Certificate Machine Learning: Home Health
-- ViewingNowThe Certificate Machine Learning: Home Health is a comprehensive course designed to equip learners with essential skills in applying machine learning techniques to home health care. This course is crucial in today's industry, where there is a growing demand for professionals who can leverage data and AI to improve healthcare delivery and patient outcomes.
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• Introduction to Machine Learning: Basic concepts, types, and applications of machine learning. Understanding algorithms, models, and biases.
• Data Preprocessing for Healthcare: Data cleaning, transformation, and normalization. Handling missing data, outliers, and errors.
• Supervised Learning Techniques: Regression, decision trees, random forests, support vector machines (SVM), and k-nearest neighbors (k-NN).
• Unsupervised Learning Techniques: Clustering, dimensionality reduction, and association rules. K-means, hierarchical clustering, and principal component analysis (PCA).
• Deep Learning for Home Health: Neural networks, convolutional neural networks (CNN), and recurrent neural networks (RNN). Applications in healthcare and medical imaging.
• Time Series Analysis: Autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) models. Seasonal ARIMA and exponential smoothing.
• Evaluation Metrics: Cross-validation, confusion matrix, accuracy, precision, recall, F1 score, ROC curves, and AUC.
• Ethics and Fairness: Data privacy, confidentiality, and security. Bias, discrimination, and fairness in algorithms.
• Machine Learning in Practice: Real-world applications, deployment, and maintenance. Best practices and lessons learned.
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- ThreeFourHoursPerWeek
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